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Article

The Influence of Water Temperature on the Hydrogeochemical Composition of Groundwater during Water Extraction and Reinjection with Geothermal Heat

by
Timotej Verbovšek
Department of Geology, Faculty of Natural Sciences and Engineering, University of Ljubljana, Aškerčeva 12, 1000 Ljubljana, Slovenia
Energies 2023, 16(9), 3767; https://doi.org/10.3390/en16093767
Submission received: 14 March 2023 / Revised: 21 April 2023 / Accepted: 25 April 2023 / Published: 28 April 2023
(This article belongs to the Section J: Thermal Management)
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Abstract

:
This study presents a simulation of potential changes in groundwater in three wells within a Quaternary gravel aquifer in the city of Ljubljana when groundwater cooled by about 4 °C is reinjected into it. The research focuses on the mass transport of calcite in the vicinity of boreholes. According to our results, the impact of the changes in the geochemical composition of the water is relatively small (around 1%). Although the waters are approximately in equilibrium, calcite may be dissolved and sometimes precipitated within the aquifer when cooled water is reinjected into it. The amounts of precipitated calcite always decrease with decreasing temperatures of the reinjected water, which can lead to calcite dissolution if the temperature difference is large enough and the water is only slightly oversaturated. This novel finding is significant since previously published studies have mostly focused on understanding the scaling (precipitation) of calcite and not its dissolution. The mass transfer of calcite is relatively low, but in a scenario of long-term pumping for several years, such low values could lead to a dissolved or precipitated mass of several hundreds of kilograms of calcite per year (at a pumping rate of 46 L/s).

1. Introduction

Geothermal heat pumps, also known as ground source heat pumps, efficiently extract heat from groundwater and transfer it to building heating systems [1,2,3,4,5]. Among the different possible systems, open-loop systems interact directly with the ground and use groundwater as a heat transfer medium. The system consists of an extraction well from which the water is pumped to the surface, passed through an indoor heat exchanger, and is then reintroduced into the aquifer through a reinjection well. The groundwater is completely reinjected into the aquifer and cooled by a few degrees in the process (usually 3 to 4 °K [6]). The advantages of such a system include its high COP (coefficient of performance) values, which exceed 3 or 4 [7,8], compared to air source heat pumps [9] and the almost constant temperature of the groundwater at shallow depths. These temperatures may vary according to the climate and lithological composition, and in this study, these were more or less constant below approximately 10 to 15 m [7,10]. If the groundwater source heat pumps operate in depths that are too shallow, they become unstable, and the operational efficiency of GWSHP is constrained [11].
Such an energy production technology is environmentally friendly because, compared to other heating options, no gas/water emissions or wastes are generated during the heating process, and the aquifer budget is not affected by the reinjection of groundwater. Several studies have been conducted worldwide to investigate the regional and national potential of groundwater heat exploitation [12,13,14,15]. However, there are several potential problems associated with the installation of open-loop doublets of extraction and reinjection wells. First, the cooled water forms a cooled area (plume) within the reinjection well and disperses plume downstream, and plume can affect the extraction well if the two wells are not adequately separated. In many countries, such problems are not covered by current local, regional, or national legislation [16], and the legal status of the use of shallow geothermal energy is quite diverse [17,18,19]. Due to thermal feedback, the system then becomes unsustainable [4], which can be tested by numerical modeling [20]. Thermal interference among the GSHP systems can be studied by spectral analysis and sinusoidal regression methods [21]. Physical modeling with laboratory tests is used less commonly [22,23,24]. Therefore, the reinjection well should be placed in the gradient direction. This problem can be easily solved because the locations of both wells can be planned or predicted to avoid such problems, mostly through coupled hydrogeological and thermal modeling [25,26,27] and also by less known, but fully coupled thermo-hydraulic-mechanical modeling [28,29], which includes changes in the stress field. Instead of reinjection wells, other methods, such as artificial gabion draining, were also proposed to decrease thermal feedback risks [30]. To save the energy consumption of the groundwater pumps and to increase the coefficient of performance, a cyclic use of groundwater was proposed [31]. Most studies are focused on changes in the groundwater chemistry or the influence of the water plumes with different temperatures, and several other potential influences are more rarely considered, such as the changes to the aquifer hydrogeochemistry due to subsurface heat storage in aquifers [32,33] or temperature changes in the ground surrounding the boreholes [34].
The second problem is more complex and related to geochemistry. The geochemistry of groundwater changes when coming into contact with cooled water as a result of changes in water temperature. Even if the number of dissolved species does not change, the geochemical equilibrium of the water will be disturbed because the chemical equations depend on temperature. The effects of groundwater heat pumps on the geochemistry of groundwater include the precipitation (scaling) of various minerals, especially calcite [35,36], a well-known process that occurs at extraction wells [37,38,39], and other problems include changes in the thermal budget of the aquifer, local ecology, and hydraulic gradient [40,41]. Among the geochemical parameters, basic geochemical properties, such as pH and Eh, are critically important variables that dictate fluid–rock and fluid–steel interactions in geothermal systems [42]. Bio-clogging can also occur due to the presence of thermophilic bacteria [43]. Generally, the casing of the wells can be affected by corrosion or precipitation/incrustration, with the most problematic minerals being the iron and manganese compounds [44]. Thus, the choice of suitable casing material is crucial to avoid geochemical and technical problems [45]. In urban areas, heat extraction can pose a threat to the mineral equilibrium in aquifers [39,46,47]. Heat extraction can also be achieved with fluids other than water, such as CO2 [48]. Geochemical influences can be predicted using geochemical software such as the most commonly used PHREEQC for Windows [38,49,50,51], WATEQ4F, TOUGHREACT/TOUGH2-BIOT [52,53], or FLOTRAN [54].
This study presents a simple calculation of potential groundwater changes at three well sites in a porous gravel aquifer in the city of Ljubljana (Slovenia). In addition to geochemical modeling, this study focuses on real geochemical data obtained from the aquifer and on the potential amount of dissolution of the rocks near the wells, as well as on the saturation indices of the major minerals. The research hypothesis is that the difference in temperature of the reinjected groundwater has a significant effect on the geochemical composition of the groundwater and the mineralogical composition of the aquifer.

2. Materials and Methods

2.1. Geological and Hydrogeological Setting

The Ljubljana Basin is located in central Slovenia and represents a Plio-Quaternary depression filled with gravel from the Sava River (Ljubljana polje aquifer) with rare sand, silt, and clay intercalations (Figure 1). Tectonically, the area belongs to the external Dinarides [55]. The bedrock of the gravel consists of Carboniferous and Permian silts and shales with rare sandstone and conglomerate intercalations [56,57]. The thickness of the gravel varies, with the shallowest depths found in the northwestern part of the basin ranging from 2 to 10 m, and the deepest depths occurring in the central part of the basin in the northern part of the city of Ljubljana, ranging from 70 to 105 m [57]. The thickness of the gravel is related to the differential subsidence and faulting of the bedrock below the gravel. The gravel deposit has a relatively high permeability and its hydraulic coefficients range from 8 × 10−3 to 3 × 10−2 m/s [58] (the specific site has a value of K = 5.73 × 10−4 m/s). The average depth of the groundwater table at the studied site is about 20 m. The average annual fluctuation of the groundwater table is about 1 m [58], but the fluctuations are greater at the studied site (more than 4 m) because the aquifer is confined in the south and unconfined in the north. In the Ljubljana city area, the southern part of the Ljubljana field aquifer in the north passes into the Ljubljana moor aquifer (Ljubljansko barje) in the south; the latter consists mainly of Quaternary lacustrine clays. The direction of groundwater flow in the Ljubljana field aquifer (Ljubljansko polje, northern part of the city of Ljubljana) is generally from W to E. In certain places, groundwater additionally flows from S to N, as a result of the inflow of water between two hills (Rožnik and Ljubljana Castle Hill) consisting of Carboniferous and Permian silts and clays. There are two aquifers in the area [59,60] that are divided by impermeable/low permeable clay and sandy clay layers that rest at depths of approximately 10 to 20 m in the study area (Figure 1D): the upper gravel aquifer, which is more heterogeneous and has greater clay contents, and the lower gravel aquifer, which has a higher hydraulic conductivity and better drinking water quality (this one is also exploited for water) [59]. The upper aquifer is influenced by the industrial area of Ljubljana and by urbanization and is recharged from the N and NW direction. The lower aquifer is recharged from the S and SE from the Ljubljana moor direction and by the smaller Gradaščica River, as well as by meteoric waters from the Rožnik hill. Due to the low permeability of clay lenses and beds, the hydrological communication between these aquifers is negligible within the area and water flows horizontally; a vertical gradient was only detected in the upper aquifer as a result of pumping. In general, the geochemical characteristics of the groundwater in the area of the Ljubljansko field aquifer do not present a risk of possible operational problems for an open-loop geothermal system, but on the contrary, the chemical composition of the groundwater in the Ljubljansko moor aquifer indicates a risk of corrosion and/or the precipitation of minerals, which can lead to a diminished efficiency of the geothermal system [61].
Two wells (W-1 and W-2; Figure 1B) were drilled for the exploitation of groundwater for heat extraction and reinjection, and two wells (V-4 and V-8; Figure 1B) were previously drilled nearby for use by a local brewery [62,63]. Several other boreholes and piezometers were drilled at the brewery location, which are mostly used for monitoring the groundwater but are not included in this study due to the lack of geochemical data and vicinity of the abovementioned wells (V-4 and V-8). Wells W-1 and V-8 reach the Carboniferous and Permian bedrock and capture groundwater from the lower aquifer. V-4 does not reach the bedrock and previously extracted groundwater from the upper aquifer; however, after the reconstruction works on the well in 2000, the filter section was completely replaced so the exploitation is now performed in the lower aquifer. The depths of the wells range from around 50 m to 90 m.

2.2. Hydrogeochemical Data and Calculations

Groundwater analyses were performed once annually from 2012 to 2019 for pumping well V-4, once annually from 2013 to 2019 for pumping well V-8, and an analysis was conducted in 2020 for pumping well W-1. A full geochemical analysis of all major and minor elements and physical geochemical parameters (water temperature, pH, electroconductivity, dissolved oxygen, oxidation-reduction potential) was performed on-site. The analyses were carried out at an accredited national laboratory for health, environment, and food (https://www.nlzoh.si/en/, accessed on 2 April 2023). This laboratory holds the national accreditation for chemical water testing from the Slovene Accreditation (public institute authorized by the State to perform the assignments of national accreditation service; https://www.slo-akreditacija.si/?lang=en, accessed on 2 April 2023), with the accreditation code of laboratory LP-014. According to the accreditation, the methods used for the chemical analyses were based on ISO standards. For example, the trace and some of the major elements were tested by the precise and established inductively coupled plasma mass spectrometry (ICP-MS) method, covered in the ISO 17294-2:2016 standard. The precisions of each method can be found in specific ISO standards. The list of all standards would exceed the length of this paper, so the reader is thus referred to the accreditation document for the used laboratory for further details [64]. Prior to further analyses, the water samples were analyzed for their analytical errors and were considered suitable if the error was below the 5% threshold. This error is automatically calculated in PHREEQC for Windows software code [65,66] when performing any geochemical calculations and is based on electroneutrality. The formula used was error (%) = 100 × (Cat − |An|)/(Cat + |An|), with Cat and An being the sums of cations and anions in milliequivalent units. The values below the detection limit (LOD) were replaced by the factor LOD/√2 [67]. Geochemical calculations were then performed using the PHREEQC software for Windows, which uses the PHREEQC code [65,66] to calculate saturation indices, partial pressures of CO2, and other geochemical parameters. The Lawrence Livermore National Laboratory (LNLL) geochemical database was used because it covers the largest number of species considered in this study.
For the geochemical calculations, 14 analyses were selected from all 15 available annual measurement analyses (Table 1), including a single analysis from well W-1 (water sample from 2020), six analyses from well V-4 (in 2012, 2013, 2016 to 2019), and seven analyses from well V-8 (2013 to 2019). Of the seven available analyses at site V-4, the analysis for the year 2017 was chosen as being representative and is presented in Table 1 because it was most geochemically similar to site W-1; moreover, the analytical error was relatively small (around 1.5%). The 2014 analysis from the V-4 well was the only one whose error exceeded the 5% threshold above which the analysis was considered unreliable. At well V-8, all analyses had an error of less than 5%, and the 2014 analysis was selected as being representative because all analyses were quite similar geochemically and the latter had the lowest analytical error (−0.37%). Most of the analyses (10 of valid 14) were performed during the same season, namely in September or October, with two analyses conducted in December, and only two in May.
The effect of temperature changes was simulated in PHREEQC by adjusting the reaction temperatures in 0.5 °C decrements from the initial groundwater temperature (11.8 °C for W-1 and 12.1 °C for V-4 and V-8) to the final temperature of 8 °C, corresponding to a cooling of approximately 4 °C during the reinjection process.
The workflow of the modeling was the following: water analyses were prepared in MS Excel, and all values below the LOD were replaced by the factor LOD/√2, as mentioned above. Tables were then converted into text files and used in the PHREEQC [65,66], where the water was initially checked for its saturation indices. Then, the modeling with different temperature decrements was performed, with water in equilibrium with calcite to determine the amount of dissolved/precipitated calcite (PHREEQC keywords REACTION_TEMPERATURE and EQUILIBRIUM_PHASES).

3. Results and Discussion

3.1. Saturation Indices and General Geochemistry of the Water

According to the results, all analyses have a small analytical error (less than ±5%, with one exception; Table 1). The calcite saturation indices are mostly slightly positive and close to zero (Figure 2A), while the dolomite saturation indices are greater and around one (Figure 2B). Both can be considered equilibrium values, and the waters are in geochemical equilibrium with both minerals due to the carbonate-dominated composition of the aquifer. In general, there are no major differences between the groundwater compositions (Table 2). Despite the high saturation indices of the dolomite, the precipitation of this mineral is difficult, mainly due to its slow reaction kinetics [68]. This problematic precipitation is commonly referred to as ‘the dolomite problem’ [69]. The modeled partial pressures of CO2 are approximately 10−2.2 atm.
Geochemically, all analyses are very similar, as shown by the Piper plot (Figure 3). All waters belong to carbonate Ca-Mg-HCO3 facies, and the yearly analyses do not change significantly. The average pH is approximately 7.5, and does not vary significantly (Table 2), so the waters are generally not corrosive. This finding agrees with those of Koren and Janža [61], where waters in the studied area were considered non-corrosive. Regarding the iron hydroxides, no geochemical problems due to dissolved iron are expected [61] since the Fe2+ ion is not expected to form due to the relatively high pH and oxygen values of the water.

3.2. Changes in Geochemistry Due to the Reinjection of Cooled Water

The simulation of different ion concentrations of groundwater when cooler water is reinjected into the aquifer (Table 3) shows that generally, cooling does not seem to have a significant effect on the composition of the water itself since the values of the main elements change only by up to 1% (lowest row in the table). Only the concentrations of Ca2+, HCO3−, and SO42− are affected by cooling since the equilibrium in this simulation is fixed only for calcite. The modeled precipitation or dissolution of this mineral, therefore, only influences the constitutional ions (Ca2+ and HCO3−) of the modeled mineral and, consequently, the sulfate concentrations due to changes in Ca2+ contents. Table 3 shows the amount of calcite that would dissolve when the water is in equilibrium with calcite (the likely dominant mineral in the aquifer). Additionally, it was found that heavy metals have a very low reactivity or response to the temperature changes in the water when using intensive groundwater heat pump systems [70].

3.3. Calcite Mass Transfer for Pumping Scenarios

An example of the mass transfer of calcite is first provided for a scenario of discharge of Q = 10 L/s during the seven-month period of heating (October to April, the heating period for Ljubljana) and a daily operational time of the submersible pump of six hours (personal experience with a groundwater source heat pump), and then for a scenario for a discharge Q = 46 L/s within the same period. The first discharge corresponds to a smaller ‘normal’ pumping rate for a submersible pump, and the larger discharge to a proposed value of a total of 46 L/s, as planned with future pumping from two (or three if two would be insufficient) pumping wells, each producing from 10 to 25 L/s. In the long term, both scenarios may be problematic because such reinjection would dissolve a large number of carbonates, leading to possible subsidence and engineering problems in the injection well area. Interestingly, both outcomes (dissolution and precipitation) appear in the same well for different analyses (different years). This can be attributed to the initial conditions related to the analytical error. Indeed, slight deviations from the strict theoretical geochemical equilibrium can occur even if the error is very small, and this positive or negative sum of cations or anions can cause positive or negative mass transfer values. However, small analytical errors do not influence the outcome of the study, which is the already mentioned very small change in the geochemical composition of groundwater due to cooling.
Another outcome of the modeling is that with decreasing injection temperatures, all of the calcite mass transfer has a negative trend, resulting in the even greater dissolution of the already dissolved calcite (the lowest curves in Figure 4), and progressively lower values of precipitated calcite above the equilibrium line (Figure 4).
The amount of dissolved calcite, therefore, increases as the temperature of the reinjected groundwater decreases, and although the changes in water composition (major ions) are small (Table 3), the long-term dissolution of calcite may occur if the groundwater is initially balanced with this mineral, as discussed at the beginning of this section. The analysis of the water from well V-4 in 2017, for example, shows that the composition of the latter is closest to equilibrium since its saturation index for calcite is almost zero (Table 1). Although the measured mass transfer of calcite is initially slightly positive (0.04 mg/L), it drops to a negative value (−0.01 mg/L) in the next step and becomes even more negative, reaching a final value of −1.09 mg/L, as the reinjection temperature decreases. Approximately 400 kg of calcite would be dissolved in water in the scenario with a pumping discharge of 46 L/s (Figure 5).
Regarding the analyses for well V-8 in the year 2014, the modeling results show relatively small changes in groundwater composition during the cooling simulation; however, the precipitation of calcite occurs instead of its dissolution (ΔCalcite is positive throughout the simulation). This occurs due to the initial largest saturation index. The amount of calcite precipitated in this simulation is also relatively low (3.48 mg/L), but this results in 736 kg of precipitated calcite for the pumping rate of 46 L/s. The amount of precipitated calcite decreases with temperature (Figure 3), and in the case of a much larger temperature difference, precipitation would cease, and the process of dissolution would begin.
The interpretation of calcite is quite sensitive to the initial conditions, i.e., the analytical errors associated with each studied well. When the geochemical scenarios are examined, the results for the mass transfer of calcite are quite different. Indeed, different models suggest different outcomes (i.e., dissolution or precipitation; Figure 5), and consequently, the analyses obtained during different periods can yield different mass transfer values (for example the two analyses in the year 2018, Figure 5). However, the trend always shows a decrease in calcite mass transfer with decreasing temperatures of the reinjected groundwater, regardless of the analysis.
In reality, the reinjected water will be mixed with the original aquifer water and will change its composition. However, to model such mixing, a ratio between both groundwaters should be known on the reinjection site. In addition, mixing effects would diminish in the surroundings of the borehole, and analysis of such mixing influence would also require hydrogeological data and modeling, which is outside the scope of this paper. Nevertheless, the results would probably not be much different than the predicted ones, especially out of the immediate vicinity of boreholes, as the amount of reinjected water in the aquifer is relatively small compared to the amount of aquifer water.
For a more detailed analysis of the possible long-term effects of reinjection, the geochemical and/or mineralogical composition of all minerals constituting the exploited aquifer at the site itself should be determined more accurately. The model used in this study is relatively simple and it only considers the balance of water with calcite (the predominant mineral) but not that of any other components. Nonetheless, the presented model with calcite only is probably quite realistic. Indeed, a model considering the mass balance of dolomite only would be geologically unrealistic and thus was not tested. Moreover, difficulties would be encountered in modeling the composition of groundwater with both calcite and dolomite since calcite dissolves much faster and in greater amounts than dolomite. Other minerals occur in the aquifer in much smaller amounts, are much less soluble, and would thus not influence the results significantly. Therefore, this is the main limitation of the presented calculations. Minor limitations can be attributed to water analysis errors (however, waters with errors greater than the 5% threshold were not considered in the calculations), the unknown mixing ratio of reinjected and original aquifer water, and long sampling intervals. Future research should, therefore, focus on the shorter sampling intervals (monthly or a few times per year), and most importantly on the evaluation of the influence of reinjected water on the aquifer, such as when the system will be put into operation and monitored, to check the validity of the modeling.

4. Conclusions

According to the modeling, the effects of cooling temperatures on the geochemical composition of the groundwater from the wells sampling the Quaternary aquifer in Ljubljana city are relatively small. The changes in the compositions ranged within 1%, which is comparable to the range of analytical errors. The reintroduction of cooler water did not result in an increase in dissolved solids above the maximum permissible level for drinking water as specified in the national rules on drinking water [71].
Regarding the energy aspect of the modeled values, the extraction and reinjection of the groundwater is feasible and the system is energetically favorable, as energy extraction does not cause major environmental disturbances. However, it is necessary to pay attention and periodically check whether there are any long-term chemical and/or mineralogical changes in the water and surrounding aquifer rock and the casing of the well.
Although the waters are at or near equilibrium, it is clear that the dissolution of calcite in the aquifer would occur in several cases, and precipitation could also occur in some scenarios. However, even with the precipitation of calcite, there is a persistent trend whereby the amount of precipitated calcite decreases with decreasing temperatures, which can lead to its dissolution if the temperature difference between the captured and reinjected groundwater is large enough and the water is only slightly oversaturated. Both processes can be problematic, resulting either in the dissolution of prevailing carbonate rocks in the aquifer, or the precipitation and clogging of the filter section and pores in the aquifer rocks. The calculations performed here are, therefore, sensitive to the initial conditions of the groundwater geochemistry, and the saturation indices are consequently slightly positive or negative.
The mass transfer of calcite is relatively low and the changes in the geochemical compositions of the groundwater samples are relatively small. However, with constant long-term pumping over several years, even such low levels of calcite in the solution could result in a dissolved or precipitated mass of several tons of this mineral. This process can be potentially problematic because such a reinjection of cooled groundwater would dissolve a large number of carbonates, which, if precipitated, could result in scaling or a less pronounced effect of calcite dissolution, potentially leading to subsidence and/or engineering problems in the area surrounding the injection well. Once a system is completed and in operation, the technical status of the wells should be periodically checked both for clogging or corrosion; groundwater samples should also be obtained regularly to allow systematical monitoring of possible water changes and to check the validity of the modeled results.
The research hypothesis is, therefore, partially confirmed. The temperature of the reinjected groundwater has a noticeable, but not significant effect on the geochemical composition of the groundwater and the mineralogical composition of the aquifer.
It should be noted that various minerals may undergo dissolution or precipitation due to natural and anthropogenic factors affecting the aquifer, but these could not be represented in this study by geochemical modeling alone.

Funding

The author acknowledges the Slovenian Research Agency (research core funding No. P1-0195 ‘Geoenvironment and Geomaterials’) for its financial support.

Data Availability Statement

Not applicable.

Acknowledgments

We thank the reviewers for their constructive comments that improved the quality of the article.

Conflicts of Interest

The author declares no conflict of interest.

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Figure 1. (A) A hydrogeological map of central Slovenia. Codes from the International Association of Hydrogeologists (IAH) are used in the legend. The 1:250,000 topographic map was provided by the Surveying and Mapping Agency of the Republic of Slovenia. (B) The study area (rectangle in region A); the blue arrows show the general direction of groundwater flow. (C) An inset map of Slovenia; the red rectangle represents the study area. (D) A hydrogeological cross-section of the brewery area (locations of wells V-4 and V-8, modified after [59]). The legend is the same as in the (A,B) sub-figures.
Figure 1. (A) A hydrogeological map of central Slovenia. Codes from the International Association of Hydrogeologists (IAH) are used in the legend. The 1:250,000 topographic map was provided by the Surveying and Mapping Agency of the Republic of Slovenia. (B) The study area (rectangle in region A); the blue arrows show the general direction of groundwater flow. (C) An inset map of Slovenia; the red rectangle represents the study area. (D) A hydrogeological cross-section of the brewery area (locations of wells V-4 and V-8, modified after [59]). The legend is the same as in the (A,B) sub-figures.
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Figure 2. Saturation indices of (A) calcite and (B) dolomite.
Figure 2. Saturation indices of (A) calcite and (B) dolomite.
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Figure 3. A Piper plot of the analyses.
Figure 3. A Piper plot of the analyses.
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Figure 4. Simulations of calcite mass transfer when water is in equilibrium with this mineral. The dashed line marks the equilibrium threshold (no dissolution or precipitation).
Figure 4. Simulations of calcite mass transfer when water is in equilibrium with this mineral. The dashed line marks the equilibrium threshold (no dissolution or precipitation).
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Figure 5. Calcite mass transfer values for scenarios of discharge Q = 10 L/s and 46 L/s (see text for details). Negative values reflect the dissolution of calcite and positive values its precipitation.
Figure 5. Calcite mass transfer values for scenarios of discharge Q = 10 L/s and 46 L/s (see text for details). Negative values reflect the dissolution of calcite and positive values its precipitation.
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Table
Table 1. Wells, sampling dates, saturation indices, and analytical errors of all available analyses. * This error exceeded the ±5% threshold level and thus, the analysis was not used for further calculations.
Table 1. Wells, sampling dates, saturation indices, and analytical errors of all available analyses. * This error exceeded the ±5% threshold level and thus, the analysis was not used for further calculations.
WellDateSelected for the Study?SIcalciteSIdolomitep(CO2) atmError%
V-421 September 2012YES0.060.7910−2.21−0.19
V-415 October 2013YES0.241.1510−2.41−3.17
V-426 September 2014NO0.271.2110−2.33+7.21 *
V-416 May 2016YES0.130.9510−2.32−0.91
V-411 October 2017YES, representative0.000.6810−2.08−1.56
V-427 September 2018YES−0.180.3210−1.89+1.18
V-425 September 2019YES0.050.7910−2.20−3.57
W-12 December 2020YES−0.020.7710−2.23−0.62
V-811 October 2013YES, max SI0.371.5310−2.49−0.95
V-826 September 2014YES, representative0.101.0110−2.23−0.37
V-811 December 2015YES−0.050.7110−2.05+4.29
V-816 May 2016YES0.261.3610−2.39+0.78
V-811 October 2017YES0.151.1310−2.28−1.85
V-827 September 2018YES, min SI−0.200.4510−1.86+0.63
V-825 September 2019YES0.241.3110−2.38−3.56
Table
Table 2. Geochemical analyses. * The detection limit was very high for these three analyses, so the value was omitted rather than being replaced by LOD/√2. ** The oxidation-reduction potential (ORP) for W-1 was calculated from the p-value (negative logarithm of the free electron concentration in the solution).
Table 2. Geochemical analyses. * The detection limit was very high for these three analyses, so the value was omitted rather than being replaced by LOD/√2. ** The oxidation-reduction potential (ORP) for W-1 was calculated from the p-value (negative logarithm of the free electron concentration in the solution).
WellW-1V-4V-4V-4V-4V-4V-4V-8V-8V-8V-8V-8V-8V-8V-4V-8
Date02.12.
2020		21.9.
2012		15.10.
2013		16.05.
2016		11.10.
2017		27.09.
2018		25.09.
2019		11.10.
2013		26.09.
2014		11.12.
2015		16.05.
2016		11.10.
2017		27.9.
2018		25.09.
2019		AverageAverage
ParameterUnit
EC (20 °C)µS/cm446432444392441416394424429409418419436442419.83425.29
Diss. O2mg/L7.796.307.507.008.747.606.306.505.798.109.009.428.408.807.248.00
ORPmV498 ** 464474 536460469.00498.00
pH /7.507.507.707.607.407.207.507.807.547.367.707.607.207.707.487.56
Temp.°C11.812.212.411.912.112.412.312.712.112.012.411.912.012.212.2212.15
NH4+mg/L 0.010.010.0060.020.0120.021<0.006<0.0060.1<0.006<0.010.120.130.010.12
HCO3−mg/L230237240234256250244253250250251256268256243.50254.86
Ca2+mg/L556561626770616262686260655864.3362.43
K+mg/L0.730.890.960.790.970.990.820.820.730.760.671.800.770.60.900.88
Cl−mg/L9.514.612.913.620.317.315.414.513.913.313.513.912.512.215.6813.40
Mg2+mg/L17.014.013.014.015.016.014.018.019.020.020.019.021.018.014.3319.29
Total Mnmg/L0.001<0.00010.0018<0.0001<0.0001<0.0001<0.00012.70.18<0.1<0.10.11<0.0001<0.0001
Na+mg/L35.65.14.98.95.65.13.53.53.83.33.53.93.45.873.56
NO3−mg/L5.306.415.745.276.806.365.666.715.595.765.565.915.795.936.045.89
NO2−mg/L0.007<0.008<0.008<0.0080.0052<0.001<0.001<0.008<0.008<0.008<0.0080.0056<0.001<0.001
PO43−mg/L0.0310.024<0.10.0510.05 <0.1<0.02<0.02<0.02<0.03
SO42−mg/L11.013.412.112.412.813.211.513.213.911.912.212.012.511.412.5712.44
Total Femg/L0.1<0.04<0.04<0.04<0.04<0.04<0.04<40 *<40 *<40 *<40 *<40 *<40 *<0.04
Asmg/L0.0010.000170.00020.000290.000210.000220.000180.000160.000160.000160.000230.000140.000160.000130.000210.00016
Bamg/L0.0120.0130.0140.0110.0140.0130.0120.0160.0170.0160.0150.0160.0170.0150.0130.016
Bmg/L0.010.0190.00860.00850.00570.00860.0130.0120.0120.0070.0130.00560.0160.0180.0110.012
Brmg/L0.015 0.220.021 0.0180.0210.1210.020
Fmg/L0.020.041<0.04<0.04<0.04<0.04<0.04<0.04<0.04<0.04<0.04<0.04<0.04<0.04
Img/L <0.05<0.05 <0.05<0.05
Total Crmg/L0.0065<0.00040.073<0.0004<0.00040.00074<0.00050.000720.00075<10<0.40.00056<0.4<0.0004
Seµg/l10.360.18 0.20.140.150.180.340.18<0.10.150.170.140.210.19
Srmg/L0.079 0.120.11 0.010.0970.120.05
Pbµg/l0.30.10.250.36<0.1<0.10.30.250.120.180.35<0.1<0.1<0.10.250.23
Alµg/l35<0.906.61.2<0.9<0.9<0.9121.21.3<0.09<0.9<0.9<0.93.904.83
Abµg/L0.10.330.0580.05<0.05<0.05<0.050.066<0.05<0.05<0.05<0.05<0.05<0.05
Cumg/L0.0010.000290.000290.00020.000190.000230.00570.00190.00160.0210.00140.0022<0.0001<0.00010.001150.00562
Beµg/L <0.04<0.04<0.04<0.04<0.04<0.04<0.04<0.04<0.04<0.04<0.04<0.04<0.04
Znµg/L10<9<9<9<9<9<0.9<9<9<9<9<9<9<0.9
Cdµg/L0.01<0.02<0.02<0.02<0.02<0.02<0.02<0.02<0.02<0.02<0.02<0.02<0.02<0.02
Coµg/L0.050.110.14<0.1<0.1<0.1<0.10.130.22<0.1<0.1<0.1<0.1<0.1
Snµg/L1<0.10.11<0.1<0.1<0.1<0.10.120.121.4<0.1<0.1<0.1<0.1
Moµg/L1<0.1<0.10.140.150.170.150.150.150.190.120.180.160.110.150.15
Niµg/L11.11.10.120.190.631.511.8<0.1<0.10.43<0.1<0.10.771.08
Vµg/L 0.240.310.220.210.19
Hgµg/L <0.015<0.015<0.01<0.01<0.01<0.01<0.015<0.015<0.01<0.01<0.01<0.01<0.01
Simg/L4.4
Table
Table 3. Major ion compositions (all data in mg/L, except temperature) of groundwater after modeling the equilibration with calcite (*, T0) and after simulating cooling to different temperatures (T1–T9). These data were modeled for well W-1 and for two representative analyses (taken in 2017 from well V-4 and in 2014 from well V-8). ** The change was calculated as the percentage difference between the final and initial scenarios divided by the initial one, for example ((Ca2+T8 − Ca2+T0)/Ca2+T0) for the calcite ion values in well W-1.
Table 3. Major ion compositions (all data in mg/L, except temperature) of groundwater after modeling the equilibration with calcite (*, T0) and after simulating cooling to different temperatures (T1–T9). These data were modeled for well W-1 and for two representative analyses (taken in 2017 from well V-4 and in 2014 from well V-8). ** The change was calculated as the percentage difference between the final and initial scenarios divided by the initial one, for example ((Ca2+T8 − Ca2+T0)/Ca2+T0) for the calcite ion values in well W-1.
W-1T (°C)Ca2+Mg2+K+Na+SO42−NO3−HCO3−Cl−ΔCalcite
T0 *11.853.1916.300.732.989.515.28225.589.50−1.17
T111.553.2416.300.732.989.525.28225.719.50−1.28
T211.053.3016.300.732.989.535.28225.929.50−1.45
T310.553.3716.300.732.989.545.28226.139.50−1.63
T410.053.4416.300.732.989.555.28226.349.50−1.80
T59.553.5016.300.732.989.565.28226.549.50−1.96
T69.053.5616.310.732.989.565.28226.749.50−2.13
T78.553.6316.310.732.989.575.28226.949.50−2.29
T88.053.6916.310.732.989.585.28227.149.50−2.46
Change **−32.2%0.9%0.1%0.0%0.0%0.7%0.0%0.7%0.0%
V-4
(2017)		T (°C)Ca2+Mg2+K+Na+SO42−NO3−HCO3−Cl−ΔCalcite
T0 *12.164.0614.330.978.8411.016.73249.8220.300.04
T112.064.0814.330.978.8411.026.73249.8820.30−0.01
T211.564.1214.330.978.8411.026.73249.9920.30−0.11
T311.064.1814.330.978.8411.036.73250.1620.30−0.25
T410.564.2714.330.978.8411.046.73250.4520.30−0.50
T510.064.3614.330.978.8411.056.73250.7320.30−0.74
T69.564.4514.340.978.8411.066.73251.0020.30−0.97
T79.064.5414.340.978.8411.076.73251.2820.30−1.21
T88.564.6314.340.978.8411.086.73251.5520.30−1.44
T98.064.7214.340.978.8411.096.73251.8220.30−1.67
Change **−33.9%1.0%0.1%0.0%0.0%0.7%0.0%0.8%0.0%
V-8
(2014)		T (°C)Ca2+Mg2+K+Na+SO42−NO3−HCO3−Cl−ΔCalcite
T0 *12.157.3518.160.733.4811.905.56237.7913.905.14
T112.057.3618.160.733.4811.905.56237.8513.905.10
T211.557.4518.160.733.4811.925.56238.0913.904.89
T311.057.5318.160.733.4811.935.56238.3413.904.68
T410.557.6118.160.733.4811.945.56238.5813.904.48
T510.057.6818.160.733.4811.965.56238.8113.904.27
T69.557.7618.170.733.4811.975.56239.0513.904.07
T79.057.8418.170.733.4811.985.56239.2813.903.87
T88.557.9218.170.733.4811.995.56239.5213.903.67
T98.057.9918.170.733.4812.015.56239.7413.903.48
Change **−33.9%1.1%0.1%0.0%0.0%0.9%0.0%0.8%0.0%
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Verbovšek, T. The Influence of Water Temperature on the Hydrogeochemical Composition of Groundwater during Water Extraction and Reinjection with Geothermal Heat. Energies 2023, 16, 3767. https://doi.org/10.3390/en16093767

AMA Style

Verbovšek T. The Influence of Water Temperature on the Hydrogeochemical Composition of Groundwater during Water Extraction and Reinjection with Geothermal Heat. Energies. 2023; 16(9):3767. https://doi.org/10.3390/en16093767

Chicago/Turabian Style

Verbovšek, Timotej. 2023. "The Influence of Water Temperature on the Hydrogeochemical Composition of Groundwater during Water Extraction and Reinjection with Geothermal Heat" Energies 16, no. 9: 3767. https://doi.org/10.3390/en16093767

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